Modelling the epidemic dynamics of COVID-19 with consideration of human mobility.

So far COVID-19 has resulted in mass deaths and huge economic losses across the world. Various measures such as quarantine and social distancing have been taken to prevent the spread of this disease. These prevention measures have changed the transmission dynamics of COVID-19 and introduced new challenges for epidemic modelling and prediction. In this paper, we study a novel disease spreading model with two important aspects. First, the proposed model takes the quarantine effect of confirmed cases on transmission dynamics into account, which can better resemble the real-world scenario. Second, our model incorporates two types of human mobility, where the intra-region human mobility is related to the internal transmission speed of the disease in the focal area and the inter-region human mobility reflects the scale of external infectious sources to a focal area. With the proposed model, we use the human mobility data from 24 cities in China and 8 states in the USA to analyse the disease spreading patterns. The results show that our model could well fit/predict the reported cases in both countries. The predictions and findings shed light on how to effectively control COVID-19 by managing human mobility behaviours.